Researchers to use brain scans to understand gender bias in software development

By | April 6, 2020
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PhD student Yu Huang poses with a helmet used for brain imaging. Huang studies how the human brain functions during different important computer science and software development tasks. (The Michigan Engineer)

A 2017 study reported that a code author’s gender had a significant impact on the code reviewer’s approval or rejection rate. In fact, women’s contributions were rejected more often when their gender was identifiable to the reviewer, and accepted more often when their work was anonymous.

An interdisciplinary team of U-M researchers will test these observations and identify some of the underlying processes that occur when a code reviewer weighs in on a piece of software and its author. Westley Weimer, professor of computer science and engineering, and PhD student Yu Huang will use medical imaging and eye tracking to better understand how gender bias impacts decisions made during code review.

Read the full article in the Michigan Engineering News Center.